Integrating GIS and Remote Sensing for Comprehensive Flood Risk Zonation in Tehsil Shah Alam (Peshawar)

Abstract

A comprehensive assessment of flood risk in tehsil Shah Alam, district Peshawar, Pakistan, was conducted using GIS and remote sensing techniques. Flooding in Pakistan is often exacerbated by human activities like deforestation and urbanization, posing significant socio-economic and environmental challenges. The study utilized 30-meter Landsat imagery, a 12.5-meter Digital Elevation Model (DEM), and rainfall data from the meteorology department to analyze critical factors influencing flood risk, including slope, river proximity, flow length, land use, and precipitation. Data processing included DEM generation, stream order classification, Euclidean distance calculation, flow length measurement, slope analysis, satellite imagery classification, and rainfall data interpolation. The Weighted Overlay Analysis (WOA) technique integrated these parameters to create a detailed flood risk zonation map. The findings highlighted areas with steep slopes, proximity to rivers, long flow lengths, high levels of built-up and barren land, and high rainfall as the most at risk. The study delineated the flood risk zones into five categories, identifying 23.28 square kilometers as very high-risk and 39.46 square kilometers as high-risk, with other areas classified into varying levels of risk. This GIS-based model offers essential insights for targeted interventions in high-risk regions, enhancing flood management and mitigation efforts.